Airbnb Price Detector

Derek Mingyu MA
derek.ma

This is a series of R programs that enables users to create initial listings URLs and update these listings' prices automatically. You can also use this R programs to grab different comprehensive information about listings on Airbnb.

Data Source

Price and Listings information is grabbed from Airbnb web app.

Set Up

A few libraries are needed. Please run the following codes to install them if you haven't

install.packages("rvest")
install.packages("httr")
install.packages("xml2")
install.packages("RSelenium")
install.packages("stringr")
install.packages("dplyr")

Function1: Create Initial Listings on Airbnb

Use the R program getInitialListings.R to get initial listings with url, city and check in/out date:

• getInitialListings.R

Following parameters need be declared at the beginning of the file:

cities

• cities that you would like to get listings
• please use the city code that Airbnb
• you can find the city code through make a query from Airbnb official web app and observe the query url

dateCheckIn

• the check in date
• please follow the format: "YYYY-MM-DD"

dateCheckOut

• the check out date
• please follow the format: "YYYY-MM-DD"

numSample

• sample size for each city

Then a csv file called listings.csv will be exported to the root directory.

Output is a csv that contain url, city and check in/out date.

Function2: Update Prices of Different Days

Input a initial listings table and get prices and total prices of listings:

• updateListings.R

Run updateListings.R and claim the previous file path at the beginning of the program.

Then the program will open corresponding pages for each listings imported from the csv file by Firefox.

The program will update the name for each listings and add two new columns to the data frame which are:

price_YYYY-MM-DD

• This is the basic price for one night
• Sometimes is NA, which is because the program cannot grab this information automatically
• There are two approaches to grab this information which are both included in the program, so that the error rate can be decreased
• YYYY-MM-DD is the date when you run this program

totalPrice_YYYY-MM-DD

• This is the price including room prices, service fee and cleaning fee
• Sometimes it can be NA, the reason is the same as the price_YYYY-MM-DD above.

Finally, a new file called listings_YYYY-MM-DD.csv will be saved to your root directory where YYYY-MM-DD is the date you run the program. The exported csv file can be used to run updateListings.R again.

Function3: Grab Comprehensive Info of Listings

Run saveInformation.R to get rating, review numbers, amenities information about the listings:

• saveInformation.R

Sample I/O File

Function 1 Sample

• Input: no need
• Output: listings.csv

Function 2 Sample

• Input: listings.csv
• Output: listings_2017-04-18.csv

Function 3 Sample

• Input: listings_1.csv
• Output: listingsInfo_1.csv